Faculty, Staff and Student Publications
Publication Date
6-8-2022
Journal
The Oncologist
Abstract
AIM: Utilization of signal detection methods in longitudinal claims data can improve post-marketing drug surveillance, but to date there has been limited application. The aim of this study is to use 3 approaches, the proportional reporting ratio, Gamma Poisson Shrinker, and tree-based scan statistic in detecting adverse drug events (ADEs) attributed to trastuzumab using an administrative claims dataset.
METHODS: Using data from the Texas Cancer Registry and SEER linked to Medicare from 2010 to 2013, we conducted 1:2 propensity score matching. Breast cancer HER2+ patients treated with trastuzumab in addition to standard chemotherapy were matched to HER2- patients treated with standard chemotherapy. Inpatient and outpatient encounters up to 6 months from start of therapy were used to identify adverse events.
RESULTS: A total of 4191 patients were included in the study. Across all methods, use of trastuzumab generated signals on 9 distinct body systems. Cardiomyopathy and heart valve disease were the most consistently detected signals. Clinical review determined that most signals represented known ADEs.
CONCLUSIONS: We showed that claims data can be used to complement current ADE monitoring using common data mining methods with propensity score matching. Our analysis identified all expected ADEs associated with trastuzumab, and additional signals of valvular heart disorders.
Keywords
Aged, Breast Neoplasms, Cohort Studies, Drug-Related Side Effects and Adverse Reactions, Female, Humans, Medicare, Trastuzumab, United States
DOI
10.1093/oncolo/oyac059
PMID
35438771
PMCID
PMC9177105
PubMedCentral® Posted Date
4-18-2022
PubMedCentral® Full Text Version
Post-print
Published Open-Access
yes
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Genetic Phenomena Commons, Medical Genetics Commons, Oncology Commons